The Spielberg Variables

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Companies want to believe that all advertising ideas—like the children of Lake Wobegone—are above average. But the bell curve dictates that only 30 out of every 100 television ads we test at consumer-products giant Unilever will be superior. Forty out of 100 will be just average, and, understandably, we don’t want to put average ads on the air.

TV commercial effectiveness is hugely important at Unilever; last year, we spent $3.3 billion globally advertising our brands. Each year, we work with our agencies to produce a multitude of 30-second spots for the U.S. market at a cost of about $400,000 each, not including airtime. Many of those ads aren’t absolute failures but still score low enough—consumers rate them as B players in quantitative research—that we would rather not entrust them with our brands. For the past few years, however, we’ve been using a diagnostic technique that allows us to reedit just-passable ads into great ones.

Working with Albuquerque, New Mexico–based Ameritest/CY Research, one of our two principal testing companies in the United States, we ask target audiences the usual questions about our ads: Do they stand out? Are they well branded? Do they motivate consumers to act? For the ads with mediocre scores, we then judge whether the problem lies with the concept (the ad looks great, but the idea isn’t exciting enough) or with the execution (the idea is potentially wonderful, but something about the way the ad was put together is holding it back). If we determine that we have a big idea hobbled by flawed execution, we put “the Spielberg variables” to work.

That is, we ensure that each of our ads employs the same style and storytelling techniques used in feature films. Good movies win viewers’ attention, propel the audience forward emotionally, and convey meaning. Good movies are also often born in the editing room. We believe the same is true of good ads, so our goal is to diagnose problems and then fix them with a new director’s cut, as it were. That requires identifying flaws at each ad’s narrative inflection points.

As a part of the process, each ad is deconstructed into frames that represent a change in tone or action—a cut to a new scene, for instance, or different body language displayed by a character in the ad. These images are randomized and shown to consumers, who have already viewed the ad in its entirety, as part of an online interview. The consumers provide three levels of feedback. First, they point out which frames they recall and which they don’t. Second, the consumers describe how they felt emotionally (Mildly positive? Strongly negative? Neutral?) about the images they recall. And finally, they talk about the values (Convenience? Taste? Nutrition?) each image conveys.

The frames give us a visual vocabulary for probing how viewers respond to discrete elements of an ad. When those data are plotted in a “flow of attention” or “flow of emotion” graph we begin to see where things go wrong. We can tell if the ad hooks viewers right away. If it doesn’t, we can pinpoint where their image recall—and hence their attention—starts to decline. Or we can see exactly where viewers shifted from a weak positive feeling to a strong one. If important information—particularly about the brand—does not appear at those points of peak attention, we are missing the boat. If viewers take away the message “cleans” when we are trying to sell them on “beauty,” we can identify exactly which images aren’t doing their jobs. Armed with this precise definition of the problem, our ad folks can make creative changes to achieve the desired effects.

Over the past two years, 60 ads from one of our health and beauty products units were approved for airing; 25 of them started out as average performers. After recutting on the basis of the Spielberg variables, those 25 ads tested in the superior range. This ability to optimize our advertising helps Unilever maximize ROI in what has traditionally been a nebulous and difficult area to measure.

John Kastenholz is the vice president of consumer insights at Unilever.

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